THE MUTUAL FUNDS OFFERED BY MAJOR SPANISH BANKS GENERATES ALFA?

JAVIER CHOLBI DOBLADO

Alt text that describes the graphic

Applied Data Science Capstone by IBM/Coursera

Introduction: Business Problem

In this project we will try to analyse if the "active" mutual funds offered by the major spanish banks generates alpha (obtain better results vs benchmark) in a consistent way along the time, in other words if it's worth to pay highers commisions for buy this mutual funds before to buy ETFs.

Our main objective its to show with data if the active management in the mutual funds industry works properly and try to answer several questions like:

  • Can the active mutual funds management by the major banks generates alfa?

  • Its better the performance in the active management vs the pasive management?

We will use our data science powers to generate a stadistical and visual analyse using some machine learning techniques as Linear and Multiple Regression.

Data and packages

Based on definition of our problem, data that will influence in our analysis are:

  • End of day historical prices of main mutual funds offered by spanish major banks from 2001 until now.

  • End of day historical prices of main index, for Europe market: EuroStoxx 50 Index.

The source of all the data used in the analysis its provided by Bloomberg across xlsx files.

Methodology

In this project we will direct our efforts in two principal axis:

  • Make a deep statistical analysis to show if there are enough evidences to affirm if spanish mutual fund management by major banks are ables to generate alfa across the time and not only in a shor period of time.

  • Make a deep visualization job using different kind of charts to ilustrate and majke easy to understand our conclusions.

Speaking about statistical techniques we are focus in:

  • Correlation historical analysis
  • Pearson coeficient
  • Matrix Correlation
  • Histogram analysis
  • Value at Risk
  • Linear Regression
  • Tracking Error Ratio
  • Sharpe Ratio
  • Alfa Ratio

Speaking about visualization we are going to use:

  • Frequency histograms
  • Boxplots charts
  • Scatter plots
  • Bubble plots
  • Area plots

Speaking about Data Science Tecniques we are going to use:

  • Data Wrangling to clean the differents datasets.
  • Data Analyst
  • Data Modelling

The analysis has 3 parts:

  • In first place clean the dataset using data wrangling techniques and explore the data using the descriptive statistical.

  • Second place, draw differents plots to understand better the information and try to see initials answer to resolve our problems.

  • Last part, use a complex stadistical techniques to make a deep analyisis that allow us to get right conclussions based on data.

Analysis:

0. Data Wranggling

  • We need to clean the dataset and drop the rows with NaN values,this it's extremely important to avoid strange results or outlier values. In this specific case there is no NaN values in the differents datasets...

1. Description information and price evolution about mutual funds in differents periods of time:

1. From the start:

Out[4]:
EURO STOXX 50 BBVA Equity Europe POPULAR Equity Europe BANKINTER Equity Europe SANTANDER Equity Europe BANKIA Equity Europe SABADELL Equity Europe CAIXABANK Equity Europe RENTA4 Equity Europe
count 4846.000000 4846.000000 4846.000000 4846.000000 4846.000000 4846.000000 4846.000000 4846.000000 4846.000000
mean 66.959048 69.665220 75.618418 83.801033 83.318663 76.566956 69.822159 74.257628 138.906676
std 12.419490 10.985152 13.765811 14.763044 18.572788 15.009538 13.251595 14.193857 41.913293
min 38.496452 38.390699 42.421048 44.234756 42.139349 40.174531 36.156250 39.954910 62.072124
25% 57.870963 61.309599 64.325704 72.156912 68.495932 63.510905 58.956236 62.511279 105.645228
50% 65.413427 70.210175 76.595583 83.588699 81.129142 78.354297 71.937135 75.722503 133.283881
75% 75.001808 77.238585 87.119095 95.670053 98.014571 89.695775 80.925183 86.164520 167.029488
max 101.824242 103.147682 103.231942 117.420704 119.208580 102.970631 100.000000 101.739618 230.736353

1.1 All the Indices vs Eurostoxx 50

2. Ten Years:

Out[7]:
EURO STOXX 50 BBVA Equity Europe POPULAR Equity Europe BANKINTER Equity Europe SANTANDER Equity Europe BANKIA Equity Europe SABADELL Equity Europe CAIXABANK Equity Europe RENTA4 Equity Europe
count 2759.000000 2759.000000 2759.000000 2759.000000 2759.000000 2759.000000 2759.000000 2759.000000 2759.000000
mean 121.766997 141.407016 130.141459 117.301344 147.662285 153.736289 149.795565 135.624213 144.571508
std 17.089281 18.144406 21.617774 16.933296 31.978004 31.199430 25.445476 24.073455 35.295105
min 73.948570 79.032734 77.716560 78.795528 74.294069 79.252048 76.831649 73.959045 74.415555
25% 110.368644 129.597999 113.677873 105.981224 120.162293 125.906447 128.425044 117.197459 114.697812
50% 122.650166 143.093681 132.352145 116.909702 153.169413 161.975543 156.082026 138.374364 141.920086
75% 135.766581 154.551166 149.847311 131.781276 178.163249 181.622937 171.625384 157.245374 169.636602
max 156.428694 181.166051 165.687155 156.700258 198.698602 203.129526 191.634979 176.037462 210.895998

2.1 All the Indices vs Eurostoxx 50

3. Five Years: We are going to make all the statistical analysis with this dataset

Out[10]:
EURO STOXX 50 BBVA Equity Europe POPULAR Equity Europe BANKINTER Equity Europe SANTANDER Equity Europe BANKIA Equity Europe SABADELL Equity Europe CAIXABANK Equity Europe RENTA4 Equity Europe
count 1455.000000 1455.000000 1455.000000 1455.000000 1455.000000 1455.000000 1455.000000 1455.000000 1455.000000
mean 106.112509 102.002247 110.795466 99.385622 112.437137 107.443459 105.465622 110.231213 125.024887
std 7.249717 6.248570 8.002966 8.039338 9.393818 7.748923 6.409257 8.461517 16.110440
min 86.212609 85.430575 89.941731 80.154345 88.252796 86.729643 88.997025 88.287729 96.604173
25% 100.078803 97.799600 103.306685 92.520953 103.605768 100.351049 99.998105 102.220813 110.435112
50% 106.286266 101.620995 111.311250 100.651119 113.838489 107.507482 105.223629 110.628466 121.136936
75% 111.965584 105.655618 118.294537 104.223965 120.920629 114.549026 111.214672 118.036046 140.465566
max 123.151496 119.578448 124.179538 120.247856 127.942755 121.339517 118.465386 124.963516 152.405700

3.1 All the Indices vs Eurostoxx 50

  • We are going to focus all the analysis in the 5 year term. This its a reasonable window for the active management inside the mutual fund industries...all the calculation are made with this temporal horizon. In this chart we can compare the differents funds in index numbers (january 2014=100), We can see that all the funds have more and less the same behaviour except the RENTA 4 fund.
  • Renta 4 has a incredible generation of alfa during this period, there are other funds with positive alfa as SANTANDER but this its not enought to affirm that both funds are a good active funds...we need to examine his stadistical behaviour...

4. Three Years:

Out[13]:
EURO STOXX 50 BBVA Equity Europe POPULAR Equity Europe BANKINTER Equity Europe SANTANDER Equity Europe BANKIA Equity Europe SABADELL Equity Europe CAIXABANK Equity Europe RENTA4 Equity Europe
count 933.000000 933.000000 933.000000 933.000000 933.000000 933.000000 933.000000 933.000000 933.000000
mean 101.034505 96.628227 101.729207 96.438272 107.165980 104.366590 98.775657 103.863321 116.309318
std 7.094406 5.339581 7.477485 6.827906 8.427435 7.714494 6.020113 8.044965 12.407593
min 82.030102 81.879869 81.728919 80.534659 81.882890 83.450930 82.754228 82.101039 84.599519
25% 93.895370 91.993704 94.151175 90.139249 99.496501 96.615397 93.121160 95.843952 104.098956
50% 102.999217 97.386841 104.219537 96.333742 109.821905 106.758288 99.867046 106.499162 121.228036
75% 106.806385 100.596155 108.048924 102.892007 114.090005 110.840282 104.022421 110.791221 125.701224
max 113.156155 107.496059 112.840384 109.515004 118.708109 116.752419 110.155497 116.206800 133.300751

4.1 All the Indices vs Eurostoxx 50

5. One Year:

Out[16]:
EURO STOXX 50 BBVA Equity Europe POPULAR Equity Europe BANKINTER Equity Europe SANTANDER Equity Europe BANKIA Equity Europe SABADELL Equity Europe CAIXABANK Equity Europe RENTA4 Equity Europe
count 412.000000 412.000000 412.000000 412.000000 412.000000 412.000000 412.000000 412.000000 412.000000
mean 96.145691 99.832720 98.390033 93.958001 98.549597 96.769352 94.037137 97.481393 100.378585
std 4.424723 4.371747 4.801967 5.998384 4.080676 4.253070 4.939029 4.509509 3.569364
min 83.829724 85.706787 84.859305 81.237122 86.659570 84.851398 79.881658 85.001754 88.774412
25% 93.833548 97.032614 95.847632 88.783488 96.103335 94.261492 90.814908 94.906655 98.119468
50% 97.065320 100.055838 99.550812 93.592088 99.461967 97.690544 94.845197 98.388107 100.588846
75% 99.308069 103.464783 102.124731 99.108536 101.788624 100.028352 97.712122 100.823096 103.265036
max 104.803993 107.602092 105.601619 106.398211 104.681701 104.413052 103.444013 104.737382 106.358158

5.1 All the Indices vs Eurostoxx 50

6. YTD: Year To Date

Out[19]:
EURO STOXX 50 BBVA Equity Europe POPULAR Equity Europe BANKINTER Equity Europe SANTANDER Equity Europe BANKIA Equity Europe SABADELL Equity Europe CAIXABANK Equity Europe RENTA4 Equity Europe
count 151.000000 151.000000 151.000000 151.000000 151.000000 151.000000 151.000000 151.000000 151.000000
mean 111.389642 112.103031 113.030051 107.668493 110.703433 111.224840 112.056043 112.208417 108.902471
std 4.874488 3.894429 5.604553 3.360778 4.508749 4.839784 4.353613 5.481191 2.737935
min 98.442071 99.069407 98.506804 98.677226 98.604477 98.874163 99.362013 98.453598 99.001629
25% 108.852643 109.998568 109.518547 105.855493 108.181299 108.406727 110.000229 108.866222 107.459145
50% 112.272858 112.308293 114.274947 107.898212 111.426812 111.908223 113.334519 113.268556 109.253331
75% 115.450020 114.834707 117.734822 110.542924 114.389325 115.571469 115.232443 116.777643 110.907918
max 118.082441 118.770808 121.081210 112.778545 117.618926 118.686048 118.058521 120.351854 113.281434

6.1 All the Indices vs Eurostoxx 50

2. Transform the 5Y dataset in daily returns to make the stadistical analyst

Out[23]:
DATES EURO STOXX 50 BBVA Equity Europe POPULAR Equity Europe BANKINTER Equity Europe SANTANDER Equity Europe BANKIA Equity Europe SABADELL Equity Europe CAIXABANK Equity Europe RENTA4 Equity Europe
1 2014-01-02 -0.015783 -0.009649 -0.010056 -0.009392 -0.012082 -0.015787 -0.007195 -0.015890 -0.011445
2 2014-01-03 0.004739 0.005317 0.005437 0.005696 0.005483 0.005707 0.010270 0.004594 0.000000
3 2014-01-06 -0.001714 -0.002084 0.000000 0.000684 -0.000006 -0.001763 -0.000376 -0.001892 0.012374
4 2014-01-07 0.013619 0.008518 0.011826 0.012952 0.008804 0.014326 0.008791 0.013599 0.019529
5 2014-01-08 -0.000096 0.000418 0.002486 0.003869 -0.000406 0.001613 0.004722 -0.000290 0.005260
Out[24]:
EURO STOXX 50 BBVA Equity Europe POPULAR Equity Europe BANKINTER Equity Europe SANTANDER Equity Europe BANKIA Equity Europe SABADELL Equity Europe CAIXABANK Equity Europe RENTA4 Equity Europe
count 1454.000000 1454.000000 1454.000000 1454.000000 1454.000000 1454.000000 1454.000000 1454.000000 1454.000000
mean 0.000144 0.000088 0.000188 0.000012 0.000206 0.000165 0.000107 0.000200 0.000296
std 0.010781 0.009861 0.009823 0.010087 0.009890 0.010474 0.009538 0.010730 0.009080
min -0.086169 -0.084448 -0.070514 -0.087759 -0.077100 -0.083487 -0.089760 -0.086153 -0.078490
25% -0.005120 -0.004373 -0.004212 -0.004535 -0.004195 -0.004778 -0.004337 -0.004879 -0.003916
50% 0.000255 0.000163 0.000000 0.000083 0.000169 0.000197 0.000368 0.000183 0.000247
75% 0.005465 0.005070 0.005018 0.004979 0.005116 0.005210 0.004848 0.005386 0.005145
max 0.047056 0.047333 0.040225 0.043944 0.044879 0.048286 0.043944 0.047381 0.035487
  • We need to transform the dataset into daily returns to analyse the statistical metrics, if we make the analysis directly with the number we are making a big mistake and wasting our time...

  • In this table we can see the mean, differents percentiles and the standard desviation.

3. Correlation Eurostoxx 50 vs Active Mutual Funds (5 Year Window)

  • The correlation between the Euro Stoxx 50 and the rest of the mutual funds are very high. The pearson ratio is higher than 90% for the vast majority, this factor its very negative in our expectatives to find a good active funds, because if the movements in the prices are very similar its very complicated to have better results vs Benchmark...the unique fund that we can consider with some difference in the returns movements its RENTA4 but we need to continue the analysis...

4. Evolution in the correlation a long time. ¿It's consistent the correlation ratios?

  • In this chart we can see the correlation not only in a point of time but in a historical range...we can see more and less the same conclusion from the previous step, but here there are two funds (SANTANDER and RENTA4) that can have at least during several time less correlations, this it's good in terms of active manegement.

5.Histogram returns and Value at Risk (VAR 95%)

*The frequency histogram are very similar in all the funds except in the RENTA4 fund, this fund has more positive tails than the others distributions and at the same time has a lower VAR ratio...this suppose a important difference and its a very important caracteristic in the active mutual funds...

6. Boxplot (How it's the behavior of the returns? Tend to zero?)

*The boxplot chart it's very useful to see how is the daily returns behavior. In our analysis we can see that almost all the funds has the same returns with a very similar interquartile range...this its very negative in terms of find active funds...due to his behaviour its the same than the benchmark index...

7. Linear Regression between Eurostoxx 50 vs Active Mutual Funds

*All the funds have a very high correlation and R2 ratio, and we can see clearly that the movements in his returns are very similar at the Euro Stoxx 50 daily returns...this give an idea about the active management grade...only the RENTA4 has a ratio lower than 80%.

8. Tracking Error Eurostoxx 50 vs Active Mutual Funds

*Normally for consider a fund as active management performance the Track error ratio needs to be higher than 6%. If we keep this idea in our mind and see the results of our analysis immediately stand out the CAIXABANK and rhe BANKIA funds because his Tracking Error ratio are close to 02...in opposite we have the Renta4 fund with a TE ratio higher than 8% given us a clearly idea about his active performance...

9. Sharpe Ratio

  • Almost the 100% of mutual funds have the same Sharpe ratio vs Eurostoxx 50 so the ratio return vs volatility its the same (so his return-risk performance its equal) this its a bad sigmal in terms of active management...but there are one fund that best this perfomance and get a better sharpe ratio: RENTA4, so this fund has better results in termns of returns asumming less risk...its clearly a example of active management.

10. Alfa Analysis

  • There are only two mutual funds that can get a positive alfa: RENTA 4 and SANTANDER, the rest of the funds don't generates consistently alfa...so if we see the results we can afirm that only a minority of mutual funds can generate alfa.

11. Mutual Fund size vs Alfa

  • There is no lineal relation between volume and alfa generation and we can't find clearly relationships between the risk and the alfa generation, so the key factor is the chief economist knowledge abaout the differents sector and corporates

Results and Discussion

Summary Table:

After our analysis we can see the results in the summary table:

Out[65]:
Mutual Fund Alfa Standar-Desviation Sharpe-Ratio Track-Error-Ratio Pearson-Ratio R2-Ratio VAR95%-Ratio
0 BBVA Equity Europe -0.075278 0.135290 -0.244579 0.087285 0.934266 87.3 -1.514373
1 POPULAR Equity Europe 0.092391 0.124299 0.187279 0.074894 0.919829 84.6 -1.603305
2 BANKINTER Equity Europe -0.188986 0.119315 -0.550266 0.066357 0.951067 90.3 -1.668539
3 SANTANDER Equity Europe 0.122363 0.118286 0.105925 0.079787 0.963157 92.7 -1.588134
4 BANKIA Equity Europe 0.040247 0.121554 0.139839 0.018571 0.990355 96.8 -1.695701
5 SABADELL Equity Europe -0.040060 0.117728 -0.209338 0.068787 0.945945 89.4 -1.499833
6 CAIXABANK Equity Europe 0.095792 0.127955 0.208462 0.006922 0.986935 95.8 -1.716250
7 RENTA4 Equity Europe 0.315127 0.112520 -0.285242 0.077958 0.893857 78.4 -1.435818

Main Results:

BBVA, SABADELL, BANKINTER:

  • This fund in the 5 year horizon dont seems to generate alfa, normally his returns are very similiar than the benchmark returns even has a worst behaviuor (alfa ratio negative).

  • In other hand the pearson correlation with the benchmark is so high (higher than 90%) and the R2 ratio is in a similar level.

  • The Value at risk its almost equal vs Benchmark and happend the same with the return histogram.

  • The track error is more and less a 6% and the sharpe ratio is normally worst than benchmark.

SANTANDER, CAIXABANK,POPULAR,BANKIA:

  • This fund in the 5 year horizon seems generate a bit of alfa, normally his returns are very similiar than the benchmark.

  • In other hand the pearson correlation with the benchmark is so high (higher than 92%) and the R2 ratio is in a similar level.

  • The Value at risk its almost equal vs Benchmark and happend the same with the return histogram.

  • The track error is more and less a 8% and the sharpe ratio is normally the same than benchmark.

RENTA4:

  • This fund in the 5 year horizon seems generate a lot of alfa, always his returns are better than the benchmark.

  • In other hand the pearson correlation with the benchmark is lower that the rest of the mutual funds high and the R2 ratio is the lowest too.

  • The Value at risk its almost very different vs Benchmark and happend the same with the return histogram, you can see a very different histogram form...

  • The track error is sometimes higher than 10% and the sharpe ratio is with difference better vs benchmark (less risk better results).

Conclusion

After analyser all the data and make a deep satatistical and visualization analyst we can conclude the next:

  • The vast majority of spanish mutual funds have the same behaviour vs benchmark, not only in his prices but in the performance of his returns....so this mutual funds must be consider as passive management and not worth pay highers commisions. We recommend to hire ETF before this funds.
  • The Renta 4 fund, the small fund speaking in terms of volume has show a very different behaviour, improving considerably respect the benchmark. Is the only fund that shows clearly an active management improving sistematicaly an improvment respect the benchmark...so we can recommend this fund.